Nanosecond-scale photothermal dynamic imaging

ABSTRACT

Systems and methods are provided for performing photothermal dynamic imaging. An exemplary method includes: scanning a sample to produce a plurality of raw photothermal dynamic signals; receiving the raw photothermal dynamic signals of the sample; generating a plurality of second signals by matched filtering the raw photothermal dynamic signals to reject non-modulated noise; and performing an inverse operation on the second signals to retrieve at least one thermodynamic signal in a temporal domain.

RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/881,996, filed on Aug. 5, 2022, which is related to and claims thebenefit of U.S. Provisional Application No. 63/229,841, filed on Aug. 5,2021, the entire contents of which are incorporated herein by reference.

GOVERNMENT SUPPORT

This invention was made with government support under grant numberGM136223 awarded by the National Institutes of Health. The governmenthas certain rights in the invention.

BACKGROUND

Photothermal microscopy is a versatile analytical tool to gauge opticalabsorption with extremely high sensitivity. Unlike conventionalspectroscopic methods that measure light attenuation, photothermaldetection acquires the absorption information via probing the thermaleffect by another light beam outside the absorption band. Its highsensitivity majorly benefits from a reduced background by employing amodulated heating beam and heterodyne detection of a frequency-shiftedprobe beam with a lock-in amplifier. Shot-noise limited imaging ofsingle gold nanoparticles of 1.4 nm diameter have been demonstratedusing such detection schemes. Single-molecule detection limit has beenreported as well.

Recently, an emerging label-free vibrational spectroscopic imagingmodality uses a mid-infrared (mid-IR) laser as a pump source and visiblelight as a probe. In this imaging modality, the mid-IR absorptioncontrast arises from a transient thermal field confined in theabsorber's vicinity. A submicron spatial resolution as good as 300 nm isachieved by probing such a field with tightly focused visible light.This new imaging modality enriches the photothermal techniques withenormous molecular fingerprint information and overcomes the limitationsin conventional mid-IR absorption microscopy, and near-field IRapproaches.

With the capability of submicron-chemical mapping of chemical bonds inaqueous environments, the mid-infrared photothermal imaging field hasexpanded with various innovations and applications. They includewide-field detection, optical phase detection, photoacoustic detection,synergistic integration with Raman, non-contact materialcharacterization, bio-molecular mapping, and metabolism imaging ofliving cells and other organisms.

Despite the success in the development and applications of photothermalmicroscopy, valuable information about an object's thermodynamics andthe transient photothermal process is rarely exploited. Photothermalheterodyne imaging (PHI) leveraging a lock-in approach can reveal amedium's thermal diffusivity. This approach has enabled variousapplications, including observing superconducting transition, tissuedifferentiation, and revealing membrane interface. However, lock-indemodulation typically loses all the photothermal signal's higher-orderharmonics, offering poor temporal resolution.

Thus, it is hard to use PHI to interpret a mid-infrared photothermalsignal that originates from the embedding medium and the object. In thetemporal domain, a time-gated approach employing a short pulse probe canresolve the dynamics by tuning the delay between probe and pump pulses.Yet, to acquire a complete thermodynamic spectrum depicting temperaturerise and decay at nanosecond resolution would require thousands ofrepetitive measurements, making it unsuitable for routine use.

SUMMARY

According to one aspect of the subject matter described in thisdisclosure, a method for performing photothermal dynamic imaging isprovided. The method includes the following: scanning a sample toproduce a plurality of raw photothermal dynamic signals; receiving theraw photothermal dynamic signals of the sample; generating a pluralityof second signals by matched filtering the raw photothermal dynamicsignals to reject non-modulated noise, the matched filtering performedby a comb-like passband in the frequency domain, wherein the comb-likepassband includes at least one window with a center position colocalizedat harmonic frequencies to reject non-modulated noise; and performing aninverse operation on the second signals to retrieve at least onethermodynamic signal in a temporal domain.

According to one implementation of the subject matter described in thisdisclosure, a method for performing photothermal dynamic imaging isprovided. The method includes the following: scanning a sample toproduce a plurality of raw photothermal dynamic signals; receiving theraw photothermal dynamic signals of the sample; generating a pluralityof second signals by matched filtering the raw photothermal dynamicsignals to reject non-modulated noise, the matched filtering performedby a comb-like passband in the frequency domain, wherein the comb-likepassband includes at least one window with a center position colocalizedat harmonic frequencies to reject non-modulated noise; performing aninverse operation on the second signals to retrieve a at least onethermodynamic signal in a temporal domain; determining, using the atleast one thermodynamic signal, a water background of the sample;determining a thermal decay difference between the water background andthe sample;

and suppressing, using the thermal decay difference, the waterbackground in photothermal imaging of the sample.

According to another aspect of the subject matter described in thisdisclosure, a system for performing photothermal dynamic imaging isprovided. The system includes one or more computing device processors,and one or more computing device memories coupled to the one or morecomputing device processors. The one or more computing device memoriesstoring instructions executed by the one or more computing deviceprocessors, wherein the instructions are configured to: scan a sample toproduce a plurality of raw photothermal dynamic signals; receive the rawphotothermal dynamic signals of the sample; generate a plurality ofsecond signals by matched filtering the raw photothermal dynamic signalsto reject non-modulated noise, the matched filtering performed by acomb-like passband in the frequency domain, wherein the comb-likepassband includes at least one window with a center position colocalizedat harmonic frequencies to reject non-modulated noise; and perform aninverse operation on the second signals to retrieve a at least onethermodynamic signal in a temporal domain.

According to another implementation of the subject matter described inthis disclosure, a system for performing photothermal dynamic imaging isprovided. The system includes one or more signal amplification devicesfor amplifying a plurality of raw photothermal dynamic signals. One ormore signal acquisition devices are coupled to the one or more signalamplification devices. One or more computing device processors arecoupled to the one or more signal acquisition devices. One or morecomputing device memories are coupled to the one or more computingdevice processors. The one or more computing device memories storeinstructions executed by the one or more computing device processors,wherein the instructions are configured to: scan a sample to produce theplurality of raw photothermal dynamic signals;

receive the raw photothermal dynamic signals of the sample; generate aplurality of second signals by matched filtering the raw photothermaldynamic signals to reject non-modulated noise, the matched filteringperformed by a comb-like passband in the frequency domain, wherein thecomb-like passband includes at least one window with a center positioncolocalized at harmonic frequencies to reject non-modulated noise; andperform an inverse operation on the second signals to retrieve a atleast one thermodynamic signal in a temporal domain.

According to another implementation of the subject matter described inthis disclosure, a non-transitory computer-readable storage mediumstoring instructions which when executed by a computer cause thecomputer to perform a method for performing photothermal dynamic imagingis provided. The method includes the following: scanning a sample toproduce a plurality of raw photothermal dynamic signals; receiving theraw photothermal dynamic signals of the sample; generating a pluralityof second signals by matched filtering the raw photothermal dynamicsignals to reject non-modulated noise, the matched filtering performedby a comb-like passband in the frequency domain, wherein the comb-likepassband includes at least one window with a center position colocalizedat harmonic frequencies to reject non-modulated noise; and performing aninverse operation on the second signals to retrieve at least onethermodynamic signal in a temporal domain.

Additional features and advantages of the present disclosure isdescribed in, and will be apparent from, the detailed description ofthis disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure is illustrated by way of example, and not by way oflimitation, in the figures of the accompanying drawings in which likereference numerals are used to refer to similar elements. It isemphasized that various features may not be drawn to scale and thedimensions of various features may be arbitrarily increased or reducedfor clarity of discussion.

FIGS. 1A-1C are graphs of photothermal modulation under a pulsed pumpsource, in accordance with some embodiments.

FIGS. 2A-2B are schematic diagrams of the photothermal dynamic imaging(PDI) system, in accordance with some embodiments.

FIG. 3A is a flowgraph of the digital processing used by thephotothermal imaging system, in accordance with some embodiments.

FIG. 3B is a schematic diagram of a comb-like passband used by thephotothermal imaging system, in accordance with some embodiments.

FIGS. 4A-4B are photothermal intensity images of 300 nm polymethylmethacrylate (PMMA) beads at absorption peak of 1729 cm⁻¹ and offresonant peak at 1600 cm⁻¹, in accordance with some embodiments.

FIG. 4C is a photothermal intensity image us a lock-in (LIA) basedmethod in the same field of view, in accordance with some embodiments.

FIGS. 5A-5C are graphs of the photothermal dynamic of the 300 nm PMMAbeads of FIGS. 4A-4B, in accordance with some embodiments.

FIG. 6 is a graph illustrating the spectrum profile of PMMA, inaccordance with some embodiments.

FIG. 7A is a photothermal intensity image of 300 nm and 500 nm PMMAbeads mixture at absorption peak 1729 cm⁻¹, in accordance with someembodiments.

FIG. 7B are graphs of the photothermal dynamics of 300 nm and 500 nmPMMA beads, in accordance with some embodiments.

FIG. 7C are graphs of the time-resolved energy flux function acquired byderivative over time, in accordance with some embodiments.

FIG. 7D is a decay constant map produced by the PDI system, inaccordance with some embodiments.

FIG. 7E is a histogram of the decay constant map of the selected area inFIG. 7D, in accordance with some embodiments.

FIG. 8A is a PDI acquired photothermal intensity image of U87 cancercells at 1650 cm⁻¹, in accordance with some embodiments.

FIG. 8B is a mid-infrared photothermal (MIP) image at 1750 cm−1 of alipid C═O band, in accordance with some embodiments.

FIG. 8C is a MIP spectra of locations indicated in FIGS. 8A-8B, inaccordance with some embodiments.

FIG. 8D are graphs of the thermodynamics of the locations indicated inFIGS. 8A-8B, in accordance with some embodiments.

FIG. 8E is a decay constant map at 1650 cm⁻¹ of the locations indicatedin FIGS. 8A-8B by exponential fitting, in accordance with someembodiments.

FIG. 8F is a decay constant map at 1750 cm⁻¹ of the locations indicatedin FIGS. 8A-8B by exponential fitting, in accordance with someembodiments.

FIG. 8G are graphs of the thermodynamics of the lipid droplets indicatedin FIG. 8E at 1650 cm⁻¹, in accordance with some embodiments.

FIG. 8H are graphs of the thermodynamics of the lipid droplets indicatedin FIG. 8F at 1750 cm⁻¹, in accordance with some embodiments.

FIG. 8I is a merged photothermal intensity image at 1750 cm⁻¹ with thebackground thermodynamics at 1650cm⁻¹, in accordance with someembodiments.

FIG. 8J is a merged photothermal intensity image of lipid contents at1750 cm⁻¹ with protein content at 1650 cm⁻¹, in accordance with someembodiments.

FIG. 9A is a PDI acquired photothermal intensity image of U87 cancercell at 1750 cm⁻¹, in accordance with some embodiments.

FIG. 9B is a MIP image of the same field of view as FIG. 9A at 1750 cm⁻¹acquired by lock-in with resonant amplifier, in accordance with someembodiments.

FIG. 9C is a 21st harmonic amplitude image of the U87 cancer cells atthe same field of view as in FIG. 9A, in accordance with someembodiments.

FIG. 9D are graphs of the normalized thermodynamics of the backgroundand lipid droplets at positions indicated in FIG. 9A, in accordance withsome embodiments.

FIG. 9E are transfer functions of the background and the lipid dropletswith decay constant of 5 μs and 300 ns, respectively, in accordance withsome embodiments.

FIG. 9F is an intensity profile of a line indicated in FIG. 9C atdifferent frequencies, in accordance with some embodiments.

FIG. 10 is a process flowgraph of operations included in an exampleprocess for performing photothermal dynamic imaging, in accordance withsome embodiments.

FIG. 11 is a schematic diagram of components that may be included in acomputer system shown in FIG. 2A, in accordance with some embodiments.

DETAILED DESCRIPTION

The figures and descriptions provided herein may have been simplified toillustrate aspects that are relevant for a clear understanding of theherein described devices, systems, and methods, while eliminating, forthe purpose of clarity, other aspects that may be found in typicalsimilar devices, systems, and methods. Those of ordinary skill mayrecognize that other elements and/or operations may be desirable and/ornecessary to implement the devices, systems, and methods describedherein. But because such elements and operations are well known in theart, and because they do not facilitate a better understanding of thepresent disclosure, a discussion of such elements and operations may notbe provided herein. However, the present disclosure is deemed toinherently include all such elements, variations, and modifications tothe described aspects that would be known to those of ordinary skill inthe art.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. Forexample, as used herein, the singular forms “a”, “an” and “the” may beintended to include the plural forms as well, unless the context clearlyindicates otherwise. The terms “comprises,” “comprising,” “including,”and “having,” are inclusive and therefore specify the presence of statedfeatures, integers, steps, operations, elements, and/or components, butdo not preclude the presence or addition of one or more other features,integers, steps, operations, elements, components, and/or groupsthereof. The method steps, processes, and operations described hereinare not to be construed as necessarily requiring their performance inthe particular order discussed or illustrated, unless specificallyidentified as an order of performance. It is also to be understood thatadditional or alternative steps may be employed.

Although the terms first, second, third, etc., may be used herein todescribe various elements, components, regions, layers and/or sections,these elements, components, regions, layers and/or sections should notbe limited by these terms. These terms may be only used to distinguishone element, component, region, layer or section from another element,component, region, layer or section. That is, terms such as “first,”“second,” and other numerical terms, when used herein, do not imply asequence or order unless clearly indicated by the context.

Described herein are example implementations of a mid-IR photothermaldynamic imaging (PDI) system with nanosecond-scale temporal resolutionand covering a bandwidth larger than 25 MHz. The bandwidth may bebetween 1 kHz and 1 GHz. Using a wideband voltage amplifier and amegahertz digitizer, a thermodynamic spectrum in response to a single IRpulse excitation is acquired and combined with digital signal processingto filter out the noise outside the fundamental IR modulation frequencyand harmonics. The PDI system may achieve more than a five-foldimprovement in signal-to-noise ratio (SNR) than lock-in basedphotothermal heterodyne imaging (PHI). Moreover, the PDI systemretrieves the transient thermal field properties and providesinformation on a target's physical properties and microenvironment.

The photothermal dynamics of various organelles inside a cancer cell maybe obtained using this approach. Unlike the macroscopic observation ofthe homogeneous thermal response of tissues or cells, a highlyheterogeneous chemically dependent thermal environment inside a cell maybe depicted. By harnessing the thermal decay difference between waterand biomolecules, cellular components that are difficult to be separatedfrom a water background in conventional photothermal microscopy can nowbe differentiated based on their time-resolved signatures.

Collectively, the PDI system enables direct detection of a transientphotothermal process with nanoseconds temporal resolution. Together withthe mid-IR excitation, this approach allows for nondestructiveinvestigation of the samples' intrinsic chemical and physical propertiesand enables chemical-specific transient thermal imaging applications.

The photothermal phenomenon originates from transforming absorbed photonenergy into heat through nonradiative relaxation. Under pulsed laserexcitation, shorter than thermal relaxation time absorbed energydeposits at the absorber and forms a localized thermal field. It inducesconcurrent thermoelastic deformation that modifies the local opticalrefractive index through local density change, which can be detected astime resolved photothermal signal through optical scattering. Comparedwith PHI detection of nanoparticles, there are two differences ininterpreting the mid-infrared photothermal (MIP) thermodynamics.

Firstly, MIP absorbers cannot be modeled by point heat sources in amedium, specifically in a living system. For example, the bond-selectivetarget like lipid droplets, protein aggregation, and cytoplasm arebulky. The thermodynamics are affected by both the absorbers and localmedium collectively. Secondly, given the water absorption in the mid-IRrange, both the absorbers and medium can experience temperatureelevation in an aqueous environment that affects the signal contrast.Therefore, the thermal field evolvement within heterogeneous thermaldiffusivity should be considered.

The absorber's local temperature evolvement under the mid-IR pump iscomposed of a temperature jump with the presence of a mid-IR pulse, asshown in FIG. 1A, followed by an exponential decay related to the heatdissipation, as shown in FIG. 1B. This transient process is given bysolving the following heat transfer equation:

$\begin{matrix}{{mC_{s}\frac{dT}{dt}} = {Q_{abs} - Q_{diss}}} & (1)\end{matrix}$

where m and C_(s) represent the mass and specific heat capacity of theabsorber; dT/dt is the temperature change over time; (Q_(abs)−Q_(diss))denotes the energy flux, representing the rate difference between theabsorbed and dissipated energies. The IR pulse duration (pulse width)may be between 1 ns to 1000 ns with a period between 1 μs to 100 μs.

The quantity Q_(abs) can be approximated by I_(IR)(t)σ_(abs), whereI_(IR)(t) represents the incident IR intensity over the IR pulse;σ_(abs) represents the IR absorption cross section. The heat dissipationfollows Newtown's law, Q_(diss) is driven by the temperature gradientand given by (hS[T(t)−T₉]), where h and S represent the heat transfercoefficient and effective transfer surface area from specimen toenvironment, respectively. The relationship (hS[T(t)−T₀]) is thetime-dependent temperature difference between the absorber and theambient environment T₀.

During the heating process, T(t) can be derived by solving Eq. (1) withthe initial condition T(0)=T₀ and neglect the IR pulse shape:

$\begin{matrix}{{T(t)} = {T_{0} + {\frac{I_{IR}\sigma_{abs}}{hS}( {1 - e^{{- \frac{hS}{{mC}_{s}}}t}} )}}} & (2)\end{matrix}$

When the IR pulse heating is finished, Q_(abs) becomes zero. Thetemperature changing is only driven by Q_(diss), T(t) is then solved as:

$\begin{matrix}{{T(t)} = {T_{0} + {( {T_{\max} - T_{0}} )e^{{- \frac{hS}{{mC}_{s}}}t}}}} & (3)\end{matrix}$

where Tmax is the maximal temperature of absorber after heatingfinishes.

From this model, one may find that both heating and cooling processescan be described as exponential processes with a time constant τ ofmC_(s)/hS. During the heating process, only with laser pulse duration ismuch shorter than i, the heat confinement condition is met assuming heatdiffusion is negligible, and Eq. (2) becomes to(T₀+(I_(IR)σ_(abs)/hS)t).

Otherwise, the temperature can slowly reach a plateau when absorbersapproximate their thermal equilibrium state.

As an analogy to a resistor-capacitor circuit, the quantity mC_(s) isthe thermal capacitor, and 1/hS is the thermal resistor. Eitherincrement of them would result in a considerable time constant. Theirtime constants are expected to be significant for absorbers with largeheat capacities, such as bulky water and large particles. The quantityhS is most related to the embedding medium's heat transfer capabilityand the absorber's shape. Therefore, the thermal response is tightlyconnected to the physical properties of both sample and coupledenvironment, which could be vastly different in a heterogeneous systemlike living cells.

In the frequency domain, the thermal response induced by a short pulselaser would span over a broad band, which is the result of multiplexingthe pulse frequency spectra with a transfer function of the absorber.The transfer function of a particular absorber with time constant i canbe approximated by:

$\begin{matrix}{{T(f)} = \frac{1}{1 + ( {2\pi f/\tau} )^{2}}} & (4)\end{matrix}$

This representation conveys important facts about a photothermal signal.Firstly, the absorber is a low pass filter for transient thermalperturbation, with a −3 dB cutoff frequency at ½πτ. This relationshipaddresses choosing the proper IR repetition rate for avoiding heatresidual and maintaining considerable modulation depth. Secondly, thephotothermal signal produced by IR with a repetition rate of fIR can betreated as a Fourier synthesis of such function and contains componentsat each harmonic of fIR as shown in the simulation of polymethylmethacrylate (PMMA) beads in air having diameters D=500 nm PMMA bead inFIG. 1C.

In particular, FIG. 1C shows harmonics are spread widely in thefrequency domain, with bandwidth determined by cutoff frequency. Large τresults in a narrow span. The photothermal signal becomes more like thesinusoidal wave at modulation frequency and has few higher-orderharmonics, while fast decay signals have many strong harmonicscomponents. Moreover, these features highlight the microenvironmentinfluences on conventional lock-in based MIP systems. The lock-in methodonly recovers the fundamental harmonic amplitude and misses all othersignals at harmonic frequencies, which sacrifices the sensitivity andcauses contrast distortion in a heterogeneous sample with differentthermal responses. In addition, the water background maximizes atmodulation frequency and hides the small organelles' signal with a weaksignal magnitude but loads various high-order harmonic components in thefrequency domain.

The photothermal signals are subtle and modulated over large backgroundsignals. The lock-in detection approach demodulates the signals byrejecting noise outside the modulation frequency band. However, thisnarrow band filtering technique loses the detection bandwidth andtemporal resolution. The PDI system utilizes a broadband acquisitionscheme using match filtering to suppress the noise. This way, bandwidth,temporal resolution, and sensitivity are well maintained.

FIG. 2A is a schematic diagram of an example mid-IR PDI system, used inaccordance with some embodiments. A quantum cascade laser provides apulsed mid-IR pump beam 210 that passes through a first dichroic mirror(DM1) and then is focused on a sample with a reflective objective (RL).The residual mid-IR beam 212 reflected by dichroic mirror DM ismonitored with an MCT detector. A counter propagated probe beam 214 froma continuous-wave 532 nm laser passes through a second dichroic mirror(DM2) and is focused on a water immersion objective lens (OL).Backscattered probe photons 216 are collected with a 50/50 beam splitter(BS), and forward scattered probe photons 218 are collected by thereflective objective lens (RL) and separated by a dichroic mirror (DM3).Both forward 218 and backward 216 probe photons are collected and sentto silicon photodiodes PD1 and PD2 connected to a wideband voltageamplifier 202, as shown in FIG. 2B.

FIG. 2B shows the voltage signal filtered with a low pass filter 204with a cut-off frequency of 25 MHz and sent to a highspeed digitizer(DAQ) 206 with a sampling rate of 50 million samples per second. DAQ 206has a sampling rate between 1 million samples per second and 3 billionsamples per second. A computer 208 is used to control the scan stage 209and the QCL laser synchronously. Meanwhile, a mercury cadmium telluride(MCT) detector is placed to monitor the IR pump pulse, and the signal isdigitized by the same DAQ 206 synchronously.

The acquired raw PDI data per frame is transferred from DAQ 206 to thememory of computer 208 after sample scanning is finished and processedwith custom-coded software. The whole temporal trace is segmentedaccording to an assigned pixel dwell time. Then each segment is filteredin the frequency domain with a comb-like passband with each passingwindow at the harmonic pump laser repetition rate (For laser running at100 kHz, the pass windows are chosen at 100 kHz, 200 kHz, . . . , 2 MHz,2.1 MHz). The spectrum resolution defines the window size according topixel dwell time. The number of passing harmonics decides the thermaldynamic bandwidth and influences the SNR. In this case, one may use 16order harmonics (1.6 MHz) to depict absorption contrast, giving thehighest image SNR. On the other hand, for defining a completephotothermal dynamic profile, one may use the bandwidth of 25 MHz.

FIG. 3A is a process flowgraph for performing PDI, in accordance withsome embodiments. The PDI raw data was acquired from the center of 500nm PMMA beads under the IR pump at its absorption peak of 1729 cm⁻¹(Step 302). A single pulse photothermal signal can be clearly resolvedwith a signal-to-noise ratio (SNR) over 43 without averaging using thebroadband detection scheme. This single pulse resolved capability pushesPDI to an unprecedented imaging speed with a minimum acquisition time ofa few microseconds. Practically limited by the stage scanning speed, thesignal acquired per pixel is a segment of hundreds of microseconds.Match filtering, using Fourier transform, is performed on each segmentwith a comb-like passband 310 in the frequency domain to enhance the SNR(Step 304). FIG. 3B shows the comb-like passband 310, where each window312 has a center position colocalized at harmonic frequencies in thefrequency domain to reject most of the non-modulated noise 314. Afterfiltering, a filtered photothermal signal 308 is acquired using aninverse Fourier transform (Step 306). The filtered photothermal signalis related to an X-Y-t stack reconstructed with each spatial pixelextended in the temporal domain (Step 306).

The PDI was performed on PMMA beads with a nominal diameter of 300 nm.After tuning the QCL laser to 1729 cm⁻¹, corresponding to the absorptionpeak of the C═O bonds in PMMA, a photothermal intensity image of thePMMA beads was acquired, as shown in FIG. 4A. FIG. 4A shows most of thePMMA beads reached their highest temperature at t=440 ns. FIG. 4B showsno photothermal contrast at the off-resonance mid-IR excitation of 1600cm⁻¹. FIG. 4C shows the photothermal intensity image of a conventionalMIP microscope at the excitation of 1729 cm⁻¹ having the same field ofview as FIG. 4A using a lock-in and resonant amplifier. While thelock-in method produces an SNR of 71 with a pixel dwell time of 500 μs,indicating an improvement close to five-fold in detection sensitivity.The pixel dwell time is pushed to 200 μs, and one can achieve an SNR of220 for a single PMMA bead using the PDI.

FIG. 5A shows the photothermal dynamic profile of the PMMA beads shownin FIG. 4A. The highest temporal resolution in the current PDI system isultimately limited by the photodiode response time, which is a fewnanoseconds. But due to the digitizer 206, the sampling rate of 50Msamples/second is used or 20 nanoseconds. With the acquired temporalprofile, one can quantitatively measure the thermal decay constant ofthe dissipation process after t3 when the IR pulse is finished. By usingan exponential fitting function, as shown by the dashed line 502, thefitted decay constant is 300 ns.

From Eq.3, this time constant is given by mC_(s)/hS. The heat transferparameter hS between the absorber and its microenvironment may bedetermined using the information on the material's density ρ and Cs. Inthe case of a 300 nm PMMA particle on a calcium fluoride (CaF₂)substrate, the heat transfer parameter is determined to be 7.78E-8 W/K.Using the finite element method (FEM), this parameter was determined tobe 7.65E-8 W/K, which closely matches the experimental measurement.

The time-resolved energy flux function [Qabs(t)−Qdiss(t)] in Eq.1 couldbe directly evaluated by taking the derivative of the transientphotothermal signal to time, as shown in FIG. 5B. From the model, thisfunction is written as:

$\begin{matrix}{\frac{{dI}_{MIP}}{dt} = {{\frac{\gamma}{{mC}_{s}}{I_{IR}(t)}\sigma_{abs}} - {\frac{hS}{{mC}_{s}}{I_{MIP}(t)}}}} & (5)\end{matrix}$

where

$\gamma = \frac{{dI}_{MIP}}{dt}$

is the coefficient representing the scattering intensity change perkelvin for a particular sample.

This function matched well with the IR pulse shape in experimentalresults. The thermodynamics is composed of three stages. At thebeginning of heating (from t1 to t2), the heat dissipation isnegligible. The first term that relates to the energy absorption isdominant, resulting in a pulse-like waveform similar to the IR pulseshape hR(t), as indicated in FIG. 5C. The temperature keeps rising untilthe heat dissipation term equals heat influx; at this point, the energyflux function becomes zero, and the absorber enters a thermalequilibrium state.

Due to the non-ideal IR pulse shape, the cooling process happened beforethe IR pulse was entirely finished. From t2 to t3, with the IR intensityreduced gradually, the dissipated energy becomes dominant, and theenergy flux function starts to be negative, showing the absorber hasentered the cooling stage. After the IR pulse ended (>t3), the heat fluxfunction only shows the heat dissipation term as an exponential decay.This explained why the experimentally acquired thermodynamics of the 300nm PMMA beads have a concave function-like decay at the beginning ofcooling.

The photothermal intensity was taken under different IR wavelengths tovalidate the spectral fidelity. The MIP spectrum of the 300 nm PMMAbeads was compared with the spectrum of a PMMA film acquired with FTIR,as shown in FIG. 6 . The IR laser pulse energy normalized the rawphotothermal spectra. Good consistency was observed in the entireregion.

The thermodynamic model discussed above shows that both the temperaturerise and decay are strongly related to the time constant mC_(s)/hS. Forspherical particles embedding in a uniform medium, the parameter hS canbe approximated by 2πkD, where k is the medium heat conductivity and Dis the particle diameter. As a result, the decay constant isproportional to r²ρC_(s)/k. For the particle with the same material anduniform microenvironment, the time constant has an r² dependency.Thermodynamic imaging of PMMA particles of different sizes (300 nm and500 nm) was performed to validate this relationship, as shown in FIG.7A. Except for the photothermal intensity difference, a significantdifference in their thermodynamics is observed. The thermodynamics andheat flux function of the indicated particles in FIG. 7A is shown inFIG. 7B and FIG. 7C, respectively. The retrieved decay constant for the300 nm and 500 nm particles are 290 ns and 540 ns, respectively.

The decay signal at each pixel is fitted, and a decay constant map isgenerated, indicating the thermal lifetime to perform statisticalanalysis, as shown in FIG. 7D. The histogram of the selected area in thedecay constant map is shown in FIG. 7E, where one observes two peaksrepresenting the 300 nm PMMA particles and the 500 nm PMMA particleswith center values of 280 ns and 495 ns, respectively. From this result,the decay constant is scaled 1.8 times between the 300 nm and 500 nmPMMA particles. Also, the decay constant may be scaled 2.8 times whenestimated with r² dependency.

The CaF₂ substrate has a much larger heat conductivity (9.71 W/(mK))than air (0.026 W/(mK)). This difference is caused by the influence ofvariation in the substrate-contact area of different particles. As aresult, particles in such a microenvironment would have a heterogeneousheat dissipation capability with varying sizes of surface areaattachment. As the size increases, the surface contact area of thesubstrate becomes larger, increasing the heat transfer capability oflarge particles. Indeed, from the decay constant map, one can observethe heterogeneous thermal properties of the 500 nm PMAA particles inFIG. 7D. The center region has a faster decay than the edge, where thesurface contact area is small.

A bond-selective PDI of U87 cancer cells in deuterium oxide (D₂O)phosphate buffered saline (PBS) was performed to investigate thetransient thermal response of various organelles inside the cell. Bytuning the IR to 1650 cm⁻¹ corresponding to the Amide I band,protein-rich contents inside the cells strongly contrast thephotothermal intensity map shown in FIG. 8A. The D₂O PBS is used tomaintain cell morphology and to reduce the considerable water absorptionof mid-IR at 1650 cm⁻¹.

In FIG. 8A, one can observe uniformly distributed protein contents inthe cytoplasm and a strong signal from the nucleolus. The background hasa photothermal signal but is relatively weak compared to the cells'signal. This is due to the residual water absorption at this wavenumber.By tuning the IR to 1750 cm⁻¹ corresponding to the C═O band from lipids,individual lipid droplets showed a strong signal in FIG. 8B.

Photothermal spectroscopy was performed for the lipid droplet, nucleus,cytoplasm, and background medium. The spectra for each content are shownin FIG. 8C. The spectra at the nucleus and cytoplasm showed a strongpeak in the Amide I band at 1655 cm⁻¹ and shifted Amide II band at 1450cm⁻¹ due to deuterium substitution of N—H bonds. In the spectra of thelipid droplets, a strong peak occurred at 1750 cm⁻¹, indicating a highC═O content. FIG. 8D shows the photothermal dynamics of the lipiddroplet, nucleus, cytoplasm, and background medium, respectively.

Interestingly, the spectra of the lipid droplets indicated a broad peakcentered at 1650 cm⁻¹. It matched the result of the intensity map ofFIG. 8A at 1650 cm⁻¹, where the lipid droplets become bright as well.Lipid's abnormal strong contrast at this protein band is widely observedin other reported scattering-based photothermal systems. One mayinvestigate this signal's origin by studying its transient photothermalsignals, enabled by the PDI approach described herein.

Together with the IR chemical specificity, the photothermal dynamics ofthe various subcellular components are evaluated, as shown in FIG. 8D.The results showed a distinct thermal response between differentorganelles. Lipid droplets inside cells are similar to isolatedparticles embedded in an aqueous environment. Therefore, they have arelatively fast decayed signal with a time constant of 300 ns. Nucleolusand cytoplasm with rich protein contents have slower decay signalscompared to lipid droplets, which are 2.5 μs.

Interestingly, the background at 1650 cm⁻¹ has the longest decay with adecay constant larger than 5 μs due to its large water heat capacity.For a more intuitive illustration, the decay constant map for 1650 cm⁻¹(as shown in FIG. 8E) and 1750 cm⁻¹ (as shown in FIG. 8F) was generated.From the decay maps of FIG. 8E and FIG. 8F, one can differentiate thebackground and cellular structures for their distinct thermal dynamics.A thermal boundary between cell and background medium can be observed atthe edge indicated as dash line 802 in FIG. 8E.

Lipid droplets have a decay constant ranging from 150 ns to 500 ns atthe 1750 cm⁻¹ excitation, as shown in FIG. 8F. However, the higher decayconstant of lipids is not revealed under 1650 cm⁻¹. Instead, they have adecay constant similar to the background medium. The cytoplasm andnucleus have decay constants at 2.5 μs at the 1650 cm⁻¹ excitation.

Detected signals typically originate from scattering field modulation.The scattering intensity is proportional to the (n_(s)−n_(m)), where nsand nm are the refractive indexes of the sample and background medium,respectively. This assumes the size influence is neglectable. In MIPmodulation with water absorption, both n_(s)(t) and n_(m)(t) aretime-dependent. Any of them changing can result in a scatteringintensity modulation.

The underlying dynamics of lipid droplets are plotted at excitations1650 cm⁻¹ (as shown in FIG. 8G) and 1750 cm⁻¹ (as shown in FIG. 8H).Indeed, the revealed dynamics indicate different thermal properties. At1750 cm⁻¹, lipid signals LD1, LD2, and LD3 have fast responses and decaytimes in the order of a few hundred nanoseconds. However, at 1650 cm⁻¹,lipid signals LD1, LD2, and LD3 showed a relatively slower decay with adecay constant higher than 5 μs. This transient response is similar tothe water background, as shown in the dash lines 804 in FIG. 8G.

The derivative of the time-resolved photothermal signal was taken todetermine whether this crosstalk comes from the heat exchange betweenthe water background medium and the lipids. With such different thermalproperties, the 1650 cm⁻¹ peak in lipid signals LD1, LD2, and LD3 shouldcome from the water background medium rather than the organellesthemselves. No delay longer than 20 nanoseconds is observed at 1650cm⁻¹, indicating a negligible heat diffusion during the heating andsignal generation. Therefore, the background medium is the majorcontributor to the change of nm due to water absorption.

The PDI system differentiated the signal contribution in the temporaldomain by utilizing the distinct thermal property between the waterbackground medium and lipid droplets LD1, LD2, and LD3. One cansuccessfully extract the water-induced signals of lipids LD1, LD2, andLD3 via a simple program that evaluates their photothermal intensity anddecay constant, as shown in FIG. 8I. After removing the water-inducedsignals at 1650 cm⁻¹ from the intensity image, a well-separated contentmap is acquired between lipids and proteins, as shown in FIG. 8J.

The photothermal dynamic results show lipid droplets quickly decay in afew hundreds of nanoseconds. At the same time, the water background ismuch slower, on the order of a few microseconds. By capturing thehigh-order harmonic signals, PDI further enabled us to visualize thesmall lipids 902-908, as shown in FIG. 9A. These small lipids 902-908were buried entirely in the water background when lock-in detection wasused, as shown in FIG. 9B. A Fourier analysis of the photothermaldynamic signals was performed to understand this capability better.

The transient photothermal signals of the background signal (BD)andlipid signal (LD) associated with the lipid 902-908 are shown in FIG.9C. FIG. 9C shows the fundamental components or first-order harmonics,at 100 kHz, for the background signal (BD) and lipid signal (LD)acquired by Fourier transform and plotted. The background signal (BD)and lipid signal have fast responses and present high-order harmoniccomponents. On the contrary, the water background is localized at thefundamental modulation frequency. Thus, lock-in demodulation at thefundamental frequency minimizes the contrast between lipid droplets andthe background.

The frequency responses of the background signal (BD) and lipid signal(LD)are shown in FIG. 9D. The slow background signal has components inthe first and second harmonics. As a comparison, the fast lipid signal(LD) is widely spread out in the frequency domain, with the firstharmonic only containing less than one-fifth of the total energy.Consequently, the lipid to background ratio (L/D) increases till the21st harmonic.

At the first harmonic that lock-in demodulation, the contrast is thelowest, as shown in FIG. 9D, and the lipid signal is hardly resolvedfrom the background signal. FIG. 9E shows the photothermal image of the21st harmonic (2.1 MHz), demonstrating clear contrast for small lipidswith minimal background. The intensity profiles of line 910, as shown inFIG. 9E are plotted in FIG. 9F at different frequencies. Lipid signalswith a decent lipid-to-background ratio (L/D) are shown in thehigher-order harmonics (0.7 MHz to 2.1 MHz).

FIG. 10 is a process flowgraph of operations included in an exampleprocess 1000 for performing photothermal dynamic imaging, in accordancewith some embodiments. The operations may be implemented usingcomputer-executable instructions stored on one or more non-transitorymachine-readable storage media. The instructions may be executed by oneor more processing devices, such as the processor 208, as described inFIG. 2 , to implement the operations.

Process 1000 includes scanning a sample to produce a plurality of rawphotothermal dynamic signals (Step 1002). Process 1000 includesreceiving the raw photothermal dynamic signals of the sample (Step1004). Process 1000 includes generating a plurality of second signals(such as filtered photo signals) by matched filtering the rawphotothermal dynamic signals to reject non-modulated noise. The matchedfiltering is performed by a comb-like passband (passband 302) in thefrequency domain. The comb-like passband includes at least one window(such as window 304) with a center position colocalized at harmonicfrequencies to reject non-modulated noise (such as noise 308). Process1000 includes performing an inverse operation on the second signals toretrieve at least one thermodynamic signal in a temporal domain. Process1000 includes determining, using the at least one thermodynamic signal,a water background (such as water background in FIGS. 8A-8I) of thesample (Step 310). A thermal decay difference is determined between thewater background and the sample (Step 1012). Process includessuppressing, using the thermal decay difference, the water background inphotothermal imaging (such as well-separated content map of FIG. 81 ) ofthe sample (Step 1014).

FIG. 11 is a schematic diagram of components that may be included in acomputer system 208, in accordance with some embodiments. As shown inFIG. 11 , computer system 208 includes memory 1120, which may include anon-transitory computer-readable medium such as a computer hard disk.Memory 1120 stores data 1121, computer programs 1122, and operatingsystem 1123, among other things. The operating system 1123 includes adriver, for example a kernel driver 1144, for controlling the operationsof computer system 208. Among the computer programs stored in memory1120 is computer code 1124 associated with methods 300 and 1000. Alsoincluded in computer system 208 are drive interface 1126, displayinterface 1127, keyboard interface 1128, mouse interface 1129, one ormore computer buses 1130, random access memory (RAM) 1131, processor(CPU) 1132, and graphic processing unit (GPU) 1141. The computer system208 may include a display that works in conjunction with displayinterface 1127, and a keyboard that works in conjunction with keyboardinterface 1128 for inputting text and user commands. Also, the computersystem 208 may include a mouse that works in conjunction with mouseinterface 1129 for positioning a cursor on display screen and forinputting user commands.

In some embodiments, memory 1120 may contain multiple memory componentsfor storing data. In some embodiments, RAM 1131 may contain multipleRAMs for processing computer instructions.

Processor 1132 may be a microprocessor, programmable logic, or the likefor executing computer programs, such those noted above, out of RAM1131. Processor 1132 accesses computer programs (or other data) storedon an external device via drive interface 1126. GPU 1141 is a type ofprocessing device. For example, the GPU 1141 may be a programmable logicchip that is configured to implement and to control displayfunctionality. To this end, a GPU 1141 may be programmed to renderimages, animation, and video on the computer's screen. The GPU 1141 maybe located on a plug-in card or in a chipset on the motherboard of thecomputer system, or the GPU 1141 may be in the same physical chip as theCPU 1132. In some implementations, the CPU 1132 may contain multipleCPUs. The multiple CPUs may be configured for parallel computing, insome embodiments.

The computer system 208 may have a receiver 1119, e.g., a radioreceiver, to receive and/or transmit information wirelessly or the like.Computer system 208 may also include one or more analog to digitalconverters (ADC) 1133 to convert incoming analog RF signals fromreceiver 1119 to digital samples. The computer system 208 may alsoinclude a digital signal processor (DSP) 1135 to perform digital signalprocessing operations on the digital samples. The DSP 1135 may also beoperated to improve the quality of the digital samples. The DSP may alsobe capable of executing computer programs that do not relate to signalprocessing.

Computer system 208 includes a network interface 1140, such as anEthernet port, for interfacing to a network, such as the Internet. Insome embodiments, computer system 208 may be a server connected tomultiple computer systems 208.

In some implementations, multiple electronic components, such as the GPU1141, the CPU 1132, and/or the DSP 1135, may execute one or morecomputer programs concurrently or contemporaneously. In someimplementations, the GPU 1141 may contain multiple components of eachtype shown in FIG. 11 ; for example, multiple CPUs, multiple GPUs,multiple DSPs, and so forth. One or more of each type of component maybe configured to execute one or more computer programs concurrently,contemporaneously, or simultaneously.

The disclosure describes a photothermal dynamic imaging (PDI) systemthat can sense the transient photothermal modulation with nanosecondtemporal resolution. This advanced technology enables concurrentdetection of chemically specific IR absorption and physically specificthermal dynamics at submicron spatial resolution. For the first time,one may retrieve the thermal response of various organelles inside acell. Using the PDI system, the retrieved data shows that cytoplasm,nucleus, and lipid droplets exhibit distinct time-resolved signatures.Based on the time-resolved signatures, the PDI system enabled thedifferentiation of small signals from water medium contribution.

The PDI system can improve the SNR over one order of magnitude bycapturing all the harmonics. Compared with conventional lock-inapproaches, the PDI system increases the sensitivity by more thanfour-fold for low-duty cycle photothermal signals. This improvementleverages the broad detection bandwidth for capturing all the harmonicscomponents induced by the short pulse IR pump. Notably, this approachprimarily benefits the mid-IR photothermal microscope with a powerfuloptical parametric oscillator (OPO) source, which has a pulse durationof few nanoseconds and a fixed repetition rate of tens kilohertz. Such ashort-pulsed and high peak power excitation source is highly preferredfor generating large modulation depth of small objects on athermo-conductive substrate or in an aqueous environment, where heatdissipation is relatively rapid. In such a case, the photothermal signalhas a duty cycle of less than 1%, and the lock-in amplifier can onlycapture a tiny portion of modulation.

Reference in the specification to “one implementation” or “animplementation” means that a particular feature, structure, orcharacteristic described in connection with the implementation isincluded in at least one implementation of the disclosure. Theappearances of the phrase “in one implementation,” “in someimplementations,” “in one instance,” “in some instances,” “in one case,”“in some cases,” “in one embodiment,” or “in some embodiments” invarious places in the specification are not necessarily all referring tothe same implementation or embodiment.

Finally, the above descriptions of the implementations of the presentdisclosure have been presented for the purposes of illustration anddescription. It is not intended to be exhaustive or to limit the presentdisclosure to the precise form disclosed. Many modifications andvariations are possible in light of the above teaching. It is intendedthat the scope of the present disclosure be limited not by this detaileddescription, but rather by the claims of this application. As will beunderstood by those familiar with the art, the present disclosure may beembodied in other specific forms without departing from the spirit oressential characteristics thereof. Accordingly, the present disclosureis intended to be illustrative, but not limiting, of the scope of thepresent disclosure, which is set forth in the following claims.

What is claimed is:
 1. A method for performing photothermal dynamicimaging, the method comprising: illuminating a sample with a beam ofpulsed infrared radiation to induce a transient temperature change inthe sample due to absorption of infrared radiation; illuminating atleast a portion of the infrared illuminated region of the sample with abeam of probe radiation; detecting with a photodiode at least a portionof probe beam radiation scattered from the infrared illuminated regionof the sample; digitizing an intensity of probe beam radiation detectedby the photodiode to produce a raw photothermal dynamic signal;processing a plurality of raw photothermal dynamic signal to produce asignal indicative of infrared absorption by the sample.
 2. The method ofclaim 1, wherein the processing step includes generating a plurality ofsecond signals by matched filtering the raw photothermal dynamic signalsto reject non-modulated noise.
 3. The method of claim 2, wherein thematch filtering is performed by a comb-like passband in the frequencydomain, wherein the comb-like passband includes at least one window witha center position colocalized at harmonic frequencies to rejectnon-modulated noise; and performing an inverse operation on the secondsignals to retrieve at least one thermodynamic signal in a temporaldomain.
 4. The method of claim 1, further comprising the step ofobtaining the signal indicative of infrared absorption by the sample ata plurality of positions on the sample to create an image of infraredabsorption by the sample.
 5. The method of claim 1 further comprisingthe step of obtaining the signal indicative of infrared absorption bythe sample at a plurality of wavelengths of the infrared source tocreate a signal indicative of an infrared absorption spectrum of thesample.
 6. The method of claim 1 further comprising determining, usingthe at least one thermodynamic signal, a decay constant of the sample.7. The method of claim 1 further comprising performing differentiationon the at least one thermodynamic signal to determine time-resolvedenergy flux of the sample.
 8. The method of claim 1, wherein the atleast one thermodynamic signal comprises a plurality of harmonics in thefrequency domain.
 9. The method of claim 2, wherein the at least onethermodynamic signal comprises nanosecond scale thermodynamicinformation.
 10. The method of claim 1, wherein scanning the samplecomprises subjecting the sample to a single infrared (IR) pulseexcitation with a pulse width between 1 ns to 1000 ns and a periodbetween 1 μs to 100 μs.
 11. The method of claim 2, wherein generatingthe plurality of second signals by matched filtering comprisesperforming a Fourier transform on the raw photothermal dynamic signals.12. The method of claim 1, wherein determining the water background ofthe sample comprises subjecting the sample to a single infrared (IR)pulse excitation of 1650 cm⁻¹.
 13. A system for performing photothermaldynamic imaging, the system comprising: a source of pulsed infraredradiation configured to illuminate a region of a sample to induce atransient temperature rise in the sample due to absorption of infraredradiation by the sample; a source of probe radiation configured toilluminate at least a portion of the infrared illuminated region of thesample; at least one detector configured to detect at least a portion ofprobe radiation scattered from the sample, a digitizing deviceconfigured to digitize an intensity of probe beam radiation detected bythe photodiode to produce a raw photothermal dynamic signal, and one ormore computing device processors configured to process a plurality ofraw photothermal dynamic signals to extract a signal indicative ofinfrared absorption by the sample.
 14. The system of claim 13, whereinthe one or more computing device processor are configured to generate aplurality of second signals by matched filtering the raw photothermaldynamic signals to reject non-modulated noise.
 15. The system of claim13, wherein the one or more computing device processor are configured tomatch filter the raw photothermal dynamic signals.
 16. The system ofclaim 14, wherein the one or more computing device processor areconfigured to filter the raw photothermal dynamic signals with acomb-like passband in the frequency domain.
 17. The system of claim 16,wherein the comb-like passband includes at least one window with acenter position colocalized at harmonic frequencies to rejectnon-modulated noise and to perform an inverse operation on the secondsignals to retrieve a at least one thermodynamic signal in a temporaldomain.
 18. The system of claim 13, further comprising a scan stageconfigured to enable measurements of the signal indicative of infraredabsorption by the sample at a plurality of locations on the sample. 19.The system of claim 18, wherein the source of infrared radiation is aconfigured to enable measurements of the signal indicative of infraredabsorption by the sample at a plurality of infrared wavelengths
 20. Thesystem of claim 13, wherein the instructions are further configured todetermine, using the at least one thermodynamic signal, a decay constantof the sample.
 21. The system of claim 13, wherein the instructions arefurther configured to perform differentiation on the at least onethermodynamic signal to determine time-resolved energy flux of thesample.
 22. The system of claim 14, wherein while generating theplurality of second signals by matched filtering, the instructions areconfigured to perform match filtering at a fundamental frequency andharmonics of infrared (IR) modulation frequency.
 23. The system of claim13, wherein the at least one thermodynamic signal comprises nanosecondscale thermodynamic information.
 24. The system of claim 13, whereinwhile scanning the sample, the instructions are configured to subjectthe sample to a single infrared (IR) pulse excitation.
 25. The system ofclaim 14, wherein while generating the plurality of second signals bymatched filtering, the instructions are configured to perform a Fouriertransform on the raw photothermal dynamic signals.